Statistical Evidence Can Be Used to Prove Discrimination, But Was Not Enough in This Age Discrimination/Lay Off Case

Statistical evidence, layoffs, and age discrimination cases can be tough. Take the situation facing Schechner and Lobertini in their case against KPIX-TV. Both were television news reporters who were laid off in an across the board budget reduction. They brought a lawsuit in federal district court against KPIX-TV, alleging that they were laid off based on their age and gender.

Schechner and Lobertini put forward substantial statistical evidence that they hoped would convince a jury that their selection for layoff was discriminatory. Their lawyers hired a statistician who determined that there was a statistically significant correlation between the age of the employees and their selection for lay off.

Both the district court and the court of appeals found that the employees had not met their burden of proof and dismissed the case on summary judgment. Schechner v. KPIX-TV, 686 F.3d 1018 (Ninth Cir., May 29, 2012). Although the Ninth Circuit clarified that statistical evidence can be used to meet an employee’s prima facie burden of proof in a discrimination case and that the burden of proof is “minimal,” it still ruled against the employees in this case. The Ninth Circuit noted that the same managers who made the decision to lay off Schechner and Lobertini also made the decision to renew their employment contracts shortly beforehand and thus the TV station was entitled to the “same-actor infererence.”

This case does not really change the laws on age discrimination and indeed, it can be used to support the proposition that statistical evidence is a valid methodology to prove discrimination. However, this case is also a cautionary tale that each case must be determined on its own facts, and sometimes courts rule in ways that are unexpected – making factual decisions and interpretations that are better left to the jurors.